64 results about "Nmr data" patented technology

The invention belongs to the field of food detection, and discloses a pork tenderloin freshness multi-modal fusion detection method based on deep learning, which comprises the following steps: making a sample of a pork tenderloin freshness classification model, collecting HSI data, ultraviolet fluorescence image data, electronic nose data and LF-NMR data in the pork tenderloin storage process, and preprocessing the data; respectively designing feature extraction modules for the ultraviolet fluorescence image data and the HSI data; designing a data enhancement module based on a variational auto-encoder to enhance the sample freshness boundary recognition capability of each category; designing an improved dung beetle optimization algorithm to enhance the hyper-parameter optimization ability of the model; a UV-CNN module, an HSI-CNN module, an AAVAE module and an EDBO optimization algorithm are introduced into a BiLSTM network structure, and a CNN-AAVAE-EDBO-BiLSTM classification model of the freshness of the pork tenderloin is constructed; and testing and evaluating the accuracy of the pig tenderloin classification model.

The invention discloses a method, a device and equipment for determining mobility of shale oil. The method comprises the following steps: acquiring core parameter data and nuclear magnetic resonance data of a plurality of core samples of a target reservoir in an imbibition experiment process; determining the maximum imbibition displacement oil porosity of the plurality of core samples based on the nuclear magnetic resonance data; based on the core parameter data of the plurality of core samples and the maximum imbibition displacement oil porosity of the plurality of core samples, determining key parameters influencing shale oil mobility of the target reservoir in the core parameters of the core samples; and obtaining the value of the determined key parameter from the core parameter data, and determining the relationship between the shale oil mobility and the key parameter based on the value of the key parameter and the maximum imbibition displacement oil porosity of the plurality of core samples, so as to determine the shale oil mobility of the target reservoir based on the relationship. According to the method, the shale oil mobility is more accurate and reliable, and the practicability is higher.

The invention discloses a shale oil reservoir CO2 huff and puff miscible-phase region dynamic discrimination method. The method comprises the steps that nuclear magnetic resonance testing is conducted on a target oil reservoir core sample; the method comprises the following steps: scanning a target oil reservoir core sample, constructing a three-dimensional core pore structure model, introducing nuclear magnetic resonance data to calibrate initial fluid saturation, and establishing a dynamic displacement numerical simulation model in combination with a CO2-crude oil phase equation, an interfacial tension model and a core permeability heterogeneity parameter; designing a plurality of groups of huff and puff experiments, simulating a CO2 injection process, monitoring nuclear magnetic resonance signal changes of the rock core in a displacement process in real time, correcting fluid saturation, a pressure field and interfacial tension parameters in a dynamic displacement numerical simulation model, and dividing a miscible-phase region; and selecting an optimal development parameter combination based on mixed-phase region distribution under different transfer injection opportunities, soaking time and throughput turns. According to the method, accurate division and dynamic discrimination of the CO2 huff and puff mixed-phase region are realized.

The invention provides a traditional Chinese medicine preparation quality detection method and system based on multi-dimensional data analysis, and belongs to the technical field of traditional Chinese medicine preparation quality detection. The method comprises the following steps: acquiring mass spectrum data and nuclear magnetic resonance data of various active components in a preparation to generate a multi-dimensional chemical characteristic data set; synchronously collecting corresponding data of the medicinal raw materials, and constructing a process and environment association database; constructing a chemical and process coupling analysis model; and monitoring the production process in real time to obtain the dynamic chemical fingerprint spectrum. By constructing a full-component chemical map and associating the full-component chemical map with process and environmental parameters and combining clinical curative effect data to establish a drug effect and component response curved surface model, the limitation that only a few index components are concerned in traditional detection is broken through, so that a detection result can accurately reflect the multi-target and overall regulation characteristics of the traditional Chinese medicine preparation, and the detection accuracy is improved. The problem that the components are qualified but the curative effect is poor due to single detection dimension is avoided, and the relevance between quality detection and the clinical curative effect is remarkably improved.

The invention discloses a rapid marinating soup quality parameter acquisition method and a marinating time optimization method in a sauced product cooling process, and belongs to the technical field of sauced product production processes, and the method comprises the following steps: S1, acquiring near infrared spectrum data of a meat sample by adopting a near infrared spectrum technology; performing two-dimensional correlation analysis on the near infrared spectrum data, converting the one-dimensional spectrum data into two-dimensional correlation spectrum data, and improving the resolution of the one-dimensional spectrum data and the separation degree of overlapping peaks to obtain a two-dimensional correlation analysis result; s2, processing the two-dimensional correlation spectrum data by using a moving window technology, observing a time period in which a functional group changes along with external interference, and converting static detection of a substance into dynamic analysis to obtain a moving window technology processing result; and S3, acquiring nuclear magnetic resonance data of the meat sample by adopting a nuclear magnetic resonance technology, and reflecting the motion state of hydrogen protons. According to the invention, the meat moisture migration and fat oxidation degree can be accurately identified.

A system and method for performing a reservoir evaluation are disclosed. The method includes obtaining a nuclear magnetic resonance (NMR) dataset for a plurality of samples and obtaining an NMR log for a wellbore penetrating a reservoir. The method further includes determining a rock facies description for each sample, determining an NMR transverse relaxation time (NMR T2) distribution from the NMR dataset, and determining a set of parameters characterizing the NMR T2 distribution based on one or more predetermined parameters. The method still further includes identifying a plurality of NMR facies based, at least in part, on the set of parameters for each sample, determining a transformation that maps a subset of rock facies to a subset of the plurality of NMR facies, and performing the reservoir evaluation based, at least in part, on applying the transformation to the NMR log.

The subject invention pertains to a method that involves at least three steps: (1) acquisition of a NMR data set or spin relaxation curve for plasma, serum or whole blood samples, (2) analysis of the NMR data or relaxation curve to extract the T2 relaxation times for water (or surrogates thereof), and (3) conversion of the water T2 (or surrogates thereof) into a measure of someone's health status (referred to as a T2 health score depending on the T2 value associated with the score). The T2 health score utilizes a statistical database derived from previous studies of subjects of normal, healthy individuals to those having varying degrees of hidden or subclinical metabolic abnormalities, such as inflammation, insulin resistance, lipid abnormalities (dyslipidemia), oxidative stress or other abnormalities, and provides a measure of a subject's overall health status.

This application discloses a downhole nuclear magnetic resonance (NMR) inversion method, apparatus, equipment, and storage medium based on pruned Bayesian methods, relating to the field of NMR data processing technology. The method includes: constructing a forward dataset based on fluid relaxation time and acquisition parameters, and adding Gaussian white noise to obtain the inversion input signal; initializing prior parameters, posterior mean, and variance; constructing a kernel matrix based on relaxation time points; constructing a kernel-dictionary matrix using Gaussian functions; updating the fitted echo data and fitting residuals using hierarchical Bayesian methods, thereby updating the prior parameters; updating the posterior mean through evidence maximization and calculating the proportion of each fluid component; pruning the kernel-dictionary matrix according to a preset pruning threshold and proportion, iterating until a termination condition is met, and finally mapping to obtain a two-dimensional NMR relaxation spectrum. This method solves the problem of waiting time and loss of diffusion relaxation dimension information caused by improved logging efficiency, which makes accurate multidimensional NMR logging inversion difficult.

A method for generating a characteristic representation of a substance is described. The method comprises: obtaining one or more portions of nuclear magnetic resonance (NMR) data of the substance, wherein each NMR data portion comprises one or more NMR data sets each comprising intensity data and relaxation data, processing each NMR data portion(s) into a multidimensional distribution of fitted data sets by performing multiple fittings to a function, wherein the function comprises at least 3 fitting parameter(s), and generating the characteristic representation of the substance from the fitted data sets. The processing comprises applying at least one start guess. Each fitted data set comprises data embedding at least one fitted data subset comprising an apparent longitudinal relaxation time (T1*), an associated apparent transverse relaxation time (T2*), and an associated intensity (M0), preferably the function is a function which represents a model of the obtained NMR data portion(s).

The method for analyzing the content of D-lactic acid repeating units in polylactic acid of the present disclosure is characterized in that without special chemical treatment of polylactic acid, the content of D in polylactic acid can be quickly and accurately analyzed by using NMR data of polylactic acid and hypothetical polylactic acid.

A system and method include an analysis control unit configured to receive nuclear magnetic resonance (NMR) data of a sample. A reference database is in communication with the analysis control unit. The reference database stores standard data including information regarding a plurality of standards for chemical compounds, and may also store information regarding quantum mechanical spectral analysis (QMSA) model data and test method data. The analysis control unit is further configured to compare the NMR data with the standard data to determine if the NMR data is associated with one of the plurality of standards, and identify one or more differences between the NMR data and the one of the plurality of standards.

Systems and techniques are provided for determining a time zero echo of a nuclear magnetic resonance (NMR) sequence. An example method includes obtaining, via an NMR tool in a borehole, echo waveforms associated with refocusing pulses and a free induction decay (FID) waveform associated with an excitation pulse; determining echo values based on the echo waveforms and an apparent time-zero echo value based on the FID waveform, the apparent time-zero echo value representing a time zero echo; applying a correction factor to the apparent time-zero echo value to yield a corrected time zero echo value; and determining a spectrum associated with a sample based on an inversion performed on the corrected time zero echo values and the set of echo values before or after a conversion of the corrected time zero echo value and the set of echo values to porosity units, the conversion of the corrected time zero echo value and the set of echo values being based on one or more conversion factors.

Systems and methods for compressing nuclear magnetic resonance (NMR) data are disclosed. The methods include the steps of selecting a T1 / T2 ratio value, inverting a first portion of the echo train data using the selected T1 / T2 value, and reconstructing the inverted echo train using the selected T1 / T2 value. A quality measure is calculated based on a comparison of the reconstructed echo train to the original echo train. When the quality measure is satisfactory, the NMR data is inverted using the selected T1 / T2 value and transmitted to the surface.

The invention provides a dual-channel self-supervision pre-training method for NMR (nuclear magnetic resonance) one-dimensional spectrogram signals, which comprises the following steps of: after L2 standardization and water peak removal are performed on the NMR signals, constructing a dual-task MAE framework, inputting the first channel into Transformer by adopting Patch Embedding, and inputting the second channel into a shared encoder after extracting features through a four-stage CNN (convolutional neural network) containing InstanceeNorm1d; the double decoders reconstruct the original input respectively, wherein the CNN path uses a deconvolution network to complete up-sampling; the loss is dynamically fused by learnable weights. Meanwhile, the invention further provides a training model generated under the training method and a corresponding computer medium, by adopting InstanceNorm1d, the stability of a small batch is improved, a signal physical structure is reserved by using L2 standardization, the representation learning ability of label-free NMR data is effectively improved, and the method is suitable for downstream tasks such as disease detection and the like.

The present invention provides a multi-dimensional nuclear magnetic resonance method for rapidly evaluating organic matter in shale. The method includes the following steps: designing a nuclear magnetic resonance pulse sequence and collecting data to obtain nuclear magnetic resonance data; processing the nuclear magnetic resonance data to obtain T<subgt;1< / subgt>-T<subgt;2< / subgt;<supgt;*< / supgt> imaging; interpreting the nuclear magnetic resonance data and correlating it with organic matter. Further, a device for rapidly evaluating organic matter in shale is provided. This application can rapidly evaluate the distribution and overall content of organic matter in shale, and can provide rapid imaging for nuclear magnetic resonance instruments with different field strengths and different configurations, and is used to precisely measure the organic matter content and spatial distribution in samples of tight shale oil and gas reservoirs. This application can rapidly and non-destructively analyze to obtain the T<subgt;1< / subgt> and T<subgt;2* values and imaging results of tight shale samples, and further can characterize important information such as the internal structure, micropore characteristics, and occurrence status of saturated fluids in the samples, and has important application value in the analysis of complex samples in unconventional oil and gas reservoirs.

The invention discloses a low-field NMR relaxation time correlation spectrum reconstruction method based on deep learning, and the method comprises the steps: obtaining a sample pair which comprises original TD-NMR data, corresponding noiseless TD-NMR data and an NMR relaxation time correlation spectrum label, building a deep neural network model which comprises a convolution denoising module and a GViT inversion module, and carrying out the reconstruction of a low-field NMR relaxation time correlation spectrum. A total loss function including denoising loss, inversion loss and forward modeling loss is constructed, and robust reconstruction from original TD-NMR data with a low signal-to-noise ratio to a high-precision two-dimensional NMR relaxation time correlation spectrum is achieved. According to the method, the problems of high calculation cost, long time consumption and poor reconstruction effect on the two-dimensional relaxation time correlation spectrum of the low-signal-to-noise-ratio TD-NMR data in the traditional inversion technology are effectively solved.

The invention provides a three-dimensional nuclear magnetic resonance detection device, system and method, and relates to the technical field of porous cultural relic detection, the device comprises a frame structure, a nuclear magnetic resonance probe, a displacement module, an industrial control computer and an electron spectrometer module; the nuclear magnetic resonance probe is arranged on the displacement module and used for collecting nuclear magnetic resonance data of the porous cultural relics; the displacement module is arranged on the front side of the frame structure and is used for driving the nuclear magnetic resonance probe to move; the back side of the frame structure is provided with an industrial control computer and an electron spectrometer module, and the industrial control computer is electrically connected with the electron spectrometer module and used for sending out a control instruction and receiving, processing and displaying data; the electron spectrometer module is electrically connected with the nuclear magnetic resonance probe and the displacement module and used for sending instructions to the nuclear magnetic resonance probe and the displacement module and transmitting collected detection data to the industrial control computer. The weathering and erosion degrees in the range from the surface of the porous cultural relic to the shallow layer are quantitatively described, and data support is provided for later cultural relic protection and cultural relic restoration.

Systems and methods for compressing nuclear magnetic resonance (NMR) data are disclosed. The methods include the steps of selecting a T1 / T2 ratio value, inverting a first portion of the echo train data using the selected T1 / T2 value, and reconstructing the inverted echo train using the selected T1 / T2 value. A quality measure is calculated based on a comparison of the reconstructed echo train to the original echo train. When the quality measure is satisfactory, the NMR data is inverted using the selected T1 / T2 value and transmitted to the surface.

A method for establishing mathematical model of relationship between spontaneous imbibition volume and time of porous medium includes sample pretreatment, fully-saturation and centrifugal experiments and NMR T2 measurement. First, two rock core samples of predetermined size are selected for cleaning and drying. The first rock sample is vacuumed and injected with water to obtain a saturated sample for NMR T2 measurement. Then, spontaneous imbibition experiment is conducted on another sample, and T2 measurements are conducted to obtain the water distribution and migration characteristics during the imbibition process. Next, the calculation of the imbibition permeability, average capillary pressure and surface relaxivity are conducted based on the NMR data obtained from two samples. Finally, substitute these parameters into the Handy relationship to obtain a new NMR-based mathematical spontaneous imbibition model.

There are provided systems, methods, and processor-readable media for optimizing the end to end operation of a hydrocarbon processing system using NMR spectroscopy data. The hydrocarbon processing system is configured to process hydrocarbon feedstock material, via a configuration defined by a set of configuration parameters, such that one or more final products are produced. A yield prediction model is used to process NMR data obtained from an NMR scan of the feedstock material to generate yield prediction data. The yield prediction data includes predictions of product yields of various intermediate products and / or final products. An optimization module is used to process the yield prediction data predicted by the trained yield prediction model such that optimized configuration parameter data is obtained. The optimized configuration parameter data is effective for establishing an optimized configuration for operating the hydrocarbon processing system that optimizes or improves an objective metric.

Provided is a method for analyzing the content of D-lactic repeating units (D content) in polylactic acid that has a feature that the D content in polylactic acid can be quickly and accurately analyzed by using NMR data of polylactic acid and hypothetical polylactic acid without special chemical treatment for polylactic acid.

Nuclear magnetic resonance (NMR) tools collect data by transmitting excitation pulses and receiving signals stimulated by the transmitted excitation pulses. Excitation pulses are transmitted by the NMR tool at a time referred to as echo time zero. After a nuclear magnetic resonance (NMR) tool transmits excitation pulses, NMR signals stimulated by those excitation pulses are received at the NMR tool. Received signals include a ringing portion and an echo waveform. This ringing portion can prevent the NMR tool from collecting echo time zero data that is useful for determining properties of materials adjacent to the NMR tool. Systems and techniques of the present disclosure determine apparent time-zero echo values such that determinations made from collected NMR data can be more accurate.

The invention discloses a compound structure analysis method and system based on nuclear magnetic resonance data, and the method comprises the steps: receiving original nuclear magnetic resonance data, collected by a nuclear magnetic instrument, of a to-be-analyzed compound, preprocessing the original nuclear magnetic resonance data so as to convert the nuclear magnetic resonance data in a time domain form into nuclear magnetic resonance data in a frequency domain form, suppress noise interference and output a peak position list; constructing a solvent peak template matched with an actual spectrogram peak shape in the nuclear magnetic resonance data, delimiting candidate areas in the peak position list according to a configured search interval, and matching a signal of each candidate area with a signal of the solvent peak template to obtain a solvent peak; removing the solvent peak, calculating the offset between the actual chemical shift and the theoretical value, applying the offset to global chemical shift correction to obtain a chemical shift list, and performing structural analysis on the to-be-analyzed compound based on the chemical shift list. According to the invention, the problem of poor accuracy during compound structure analysis in the prior art is solved.

A subscriber identity module (SIM). The SIM comprises a processor, a non-transitory memory storing a configuration file, a wireless identity, a wireless access key, and a remote update agent stored in the non-transitory memory. When executed by the processor, the remote update agent determines that the SIM is communicatively coupled to a wireless communication network via a radio transceiver of a communication device with which the SIM is associated, in response to determining that the SIM is communicatively coupled to the wireless communication network, sends a provide local information (PLI) command to the mobile communication device to acquire network measurement results (NMR) based on the configuration file, transmits NMR data via the radio transceiver using a bearer independent protocol (BIP), receives SIM update information via the radio transceiver, and stores the SIM update information in the configuration file in the non-transitory memory.

1. Name of the designed product: multi-channel electronic spectrometer. 2. Use of the designed product: for nuclear magnetic resonance data acquisition, simultaneously acquiring multiple data to K-space, parallel receiving and processing multi-frequency signals from different atomic nuclei. 3. Design points of the designed product: in shape. 4. Picture or photo that best shows the design points: front view.

The application discloses a three-dimensional nuclear magnetic resonance rock sample fluid experiment analysis method and device based on a static gradient magnetic field, and the method comprises the following steps: performing fluid saturation treatment on a to-be-detected core, placing the treated to-be-detected core in a preset environment condition, and simulating fluid occurrence states in a reservoir under different diffusion time conditions; performing nuclear magnetic resonance experiments on the to-be-detected core based on the static gradient magnetic field at each diffusion time point, and collecting nuclear magnetic resonance echo data of the to-be-detected core at multiple different time points; performing three-dimensional inversion calculation on the nuclear magnetic resonance echo data, obtaining T1-T2-t three-dimensional distribution data, and performing visual analysis on the T1-T2-t three-dimensional distribution data, so as to represent the space-time variation characteristics of the reservoir fluid. The application combines the diffusion process of the fluid with the nuclear magnetic resonance T1-T2 distribution, forms three-dimensional nuclear magnetic resonance data, and can effectively capture the space-time variation of the complex fluid occurrence state in the unconventional oil and gas reservoir.

Systems and techniques are provided for determining a time zero echo of a nuclear magnetic resonance (NMR) sequence. An example method includes obtaining, via an NMR tool in a borehole, echo waveforms associated with refocusing pulses and a free induction decay (FID) waveform associated with an excitation pulse; determining echo values based on the echo waveforms and an apparent time-zero echo value based on the FID waveform, the apparent time-zero echo value representing a time zero echo; applying a correction factor to the apparent time-zero echo value to yield a corrected time zero echo value; and determining a spectrum associated with a sample based on an inversion performed on the corrected time zero echo values and the set of echo values before or after a conversion of the corrected time zero echo value and the set of echo values to porosity units, the conversion of the corrected time zero echo value and the set of echo values being based on one or more conversion factors.

A method for generating a property representation of a substance is described. The method comprises: obtaining portions of one or more nuclear magnetic resonance (NMR) data of the substance, where each NMR data portion comprises one or more NMR datasets, each NMR dataset comprising intensity data and relaxation data; processing each NMR data portion into a multi-dimensional distribution of a fitting data set by performing a plurality of fits of a function, where the function includes at least 3 fitting parameters; and generating a characteristic representation of the substance from the fitting data set. The processing includes applying at least one initial guess value. Each set of fitting data comprises data embedded with at least one subset of fitting data comprising an apparent longitudinal relaxation time (T1 *), an associated apparent transverse relaxation time (T2 *) and an associated intensity (M0), preferably said function being a function of a model representing the obtained NMR data portion.

Some implementations transmit nuclear magnetic resonance (NMR) data between downhole tools and surface-based computers. A method may include generating a first vector in which each entry includes a spectrum coefficient associated with NMR echo signals. The method may include generating a cumulative sum vector in which each entry includes a sum including a spectrum coefficient of a corresponding entry in the first vector plus any spectrum coefficients of any entries that precede the first corresponding entry in the first vector. The method may include down sampling the cumulative sum vector to form a down-sampled vector including a subset of the cumulative sum vector. The method may include generating a compressed vector in which each entry includes a difference of a corresponding entry in the down sampled vector and any entry directly preceding the corresponding entry in the down sampled vector and transmitting the compressed vector over a communication channel.

The invention discloses a nuclear magnetic resonance spectrogram library construction and analysis system based on data standardization, and relates to the technical field of data analysis, the system comprises a data acquisition module, a data format conversion module, a standardization module, a spectrogram library construction module and a visual analysis module; the data acquisition module is used for acquiring original data through a nuclear magnetic instrument and marking the original data; the data format conversion module is used for preprocessing original data and converting the preprocessed data format into a data point table form data file containing chemical shift and peak intensity; the standardization module is used for respectively carrying out operation processing and cleaning processing on X-axis data representing chemical shift and Y-axis data representing peak intensity; the spectrum library construction module is used for constructing a structured nuclear magnetic spectrum database; and the visual analysis module is used for visual presentation and analysis of the spectrogram data. According to the system and the method, spectrogram library construction and data analysis of the nuclear magnetic resonance data are realized.